scholarly journals An ANN-GA Semantic Rule-Based System to Reduce the Gap Between Predicted and Actual Energy Consumption in Buildings

2017 ◽  
Vol 14 (3) ◽  
pp. 1351-1363 ◽  
Author(s):  
Baris Yuce ◽  
Yacine Rezgui
Energies ◽  
2021 ◽  
Vol 14 (15) ◽  
pp. 4541
Author(s):  
Gabriel Santos ◽  
Tiago Pinto ◽  
Zita Vale ◽  
Rui Carvalho ◽  
Brígida Teixeira ◽  
...  

Building management systems (BMSs) are being implemented broadly by industries in recent decades. However, BMSs focus on specific domains, and when installed on the same building, they lack interoperability to work on a centralized user interface. On the other hand, BMSs interoperability allows the implementation of complex rules based on multi-domain contexts. The Building’s Reasoning for Intelligent Control Knowledge-based System (BRICKS) is a context-aware semantic rule-based system for the intelligent management of buildings’ energy and security. It uses ontologies and semantic web technologies to interact with different domains, taking advantage of cross-domain knowledge to apply context-based rules. This work upgrades the previously presented version of BRICKS by including services for energy consumption and generation forecast, demand response, a configuration user interface (UI), and a dynamic building monitoring and management UI. The case study demonstrates BRICKS deployed at different aggregation levels in the authors’ laboratory building, managing a demand response event and interacting autonomously with other BRICKS instances. The results validate the correct functioning of the proposed tool, which contributes to the flexibility, efficiency, and security of building energy systems.


Author(s):  
Aria JOZI ◽  
Tiago PINTO ◽  
Isabel PRAÇA ◽  
Francisco SILVA ◽  
Brigida TEIXEIRA ◽  
...  

2018 ◽  
Vol 15 (3) ◽  
pp. 635-654 ◽  
Author(s):  
Josefa Álvarez ◽  
Franciso Chávez ◽  
Pedro Castillo ◽  
Juan García ◽  
Francisco Rodriguez ◽  
...  

In recent years, the energy-awareness has become one of the most interesting areas in our environmentally conscious society. Algorithm designers have been part of this, particularly when dealing with networked devices and, mainly, when handheld ones are involved. Although studies in this area has increased, not many of them have focused on Evolutionary Algorithms. To the best of our knowledge, few attempts have been performed before for modeling their energy consumption considering different execution devices. In this work, we propose a fuzzy rulebased system to predict energy comsumption of a kind of Evolutionary Algorithm, Genetic Prohramming, given the device in wich it will be executed, its main parameters, and a measurement of the difficulty of the problem addressed. Experimental results performed show that the proposed model can predict energy consumption with very low error values.


2010 ◽  
Author(s):  
Ser-Huang Poon ◽  
Yu-Wang Chen ◽  
Jian-Bo Yang ◽  
Dong-Ling Xu ◽  
Dongxu Zhang ◽  
...  

2021 ◽  
Author(s):  
Nan-Nan Chen ◽  
Xiao-Ting Gong ◽  
Ying-Ming Wang ◽  
Chun-Yang Zhang ◽  
Yang-Geng Fu
Keyword(s):  

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